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论文阅读笔记《A semi-supervised CNN based method for steel surface defect recognition》
时间 2020-12-30
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论文阅读笔记
# 缺陷检测
深度学习
半监督学习
缺陷检测
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Microsoft Surface
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核心思想 本文提出一种半监督的钢铁表面缺陷检测方法(PLCNN),半监督的思路也比较常见,利用CNN对无标签样本进行预测,输出伪标签(Pseudo-Label),并将带有伪标签的样本作为训练样本对网络进行进一步训练。 网络结构的设计也没有什么特别之处,唯一有点新意的地方可能就是损失函数的设计了。 实现过程 网络结构 损失函数 损失函数包含有标签损失和无标签损失两个部分,两个部分均
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